Klasifikasi Penerima Bantuan Program Keluarga Harapan di Kenagarian Kambang Barat Menggunakan Metode Na ve Bayes Classifier

Abstract

Poverty remains a major challenge in developing countries, including Indonesia. The Family Hope Program (PKH) is a conditional assistance program from the government to improve community welfare. However, PKH distribution in Nagari Kambang Barat, Pesisir Selatan Regency, West Sumatra, still faces inaccurate targeting. This study aims to classify the eligibility of PKH recipients using the Naïve Bayes Classifier algorithm. This research is applied research, with data used in this study of 300 poor family heads. The classification results using the Naïve Bayes algorithm produced an accuracy of 81%, an error rate of 19%, a precision of 84%, a recall of 93%, and an F1-score of 88% for a 70:30 data distribution. Based on the classification results, it shows that the Naïve Bayes method is capable of classifying well in determining the eligibility of PKH recipients.